Development of Artificial Intelligence Methodologies for the Automatic Generation of Technical [...]
Descrizione dell'offerta
Organisation/Company Politecnico di Milano Research Field Engineering Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 3 Aug 2026 - 12:00 (UTC) Country Italy Type of Contract To be defined Job Status Not Applicable Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description
The research program aims to develop and validate a Proof of Concept based on Artificial Intelligence techniques for the automatic generation of technical drawings from 3D CAD models of mechanical components. The activity includes the evaluation and comparison of different AI architectures to automate the generation of views, sections, dimensions, and technical annotations while minimizing the need for manual labeling. The developed methodologies will be validated through representative case studies, comparing automatically generated drawings with those produced through traditional workflows in terms of geometric accuracy, completeness and compliance with company standards. The program also includes the definition of integration strategies into CAD tools through dedicated APIs and SDKs. Oral test aimed at ascertaining candidates' aptitude and suitability to carry out the research activity covered by the Fellowship, as well as at assessing their knowledge of English and/or other languages relevant to the research activities to be performed (up to 55 points) Relevance and pertinence of the publications, theses and scientific products attached to the research programme covered by the Fellowship (up to 15 points) Relevance and pertinence of previous research activities and work experience, if any, in relation to the research activity covered by the Fellowship (up to 10 points) Relevance and pertinence of their study programme to the research programme covered by the Fellowship (up to 20 points) E.U. Eligibility of fellows: country/ies of residence: AFRICA EUROPE OCEANIA NORTH AMERICA SOUTH AMERICA ASIA Eligibility of fellows: nationality/ies:
#J-18808-Ljbffr
The research program aims to develop and validate a Proof of Concept based on Artificial Intelligence techniques for the automatic generation of technical drawings from 3D CAD models of mechanical components. The activity includes the evaluation and comparison of different AI architectures to automate the generation of views, sections, dimensions, and technical annotations while minimizing the need for manual labeling. The developed methodologies will be validated through representative case studies, comparing automatically generated drawings with those produced through traditional workflows in terms of geometric accuracy, completeness and compliance with company standards. The program also includes the definition of integration strategies into CAD tools through dedicated APIs and SDKs. Oral test aimed at ascertaining candidates' aptitude and suitability to carry out the research activity covered by the Fellowship, as well as at assessing their knowledge of English and/or other languages relevant to the research activities to be performed (up to 55 points) Relevance and pertinence of the publications, theses and scientific products attached to the research programme covered by the Fellowship (up to 15 points) Relevance and pertinence of previous research activities and work experience, if any, in relation to the research activity covered by the Fellowship (up to 10 points) Relevance and pertinence of their study programme to the research programme covered by the Fellowship (up to 20 points) E.U. Eligibility of fellows: country/ies of residence: AFRICA EUROPE OCEANIA NORTH AMERICA SOUTH AMERICA ASIA Eligibility of fellows: nationality/ies:
#J-18808-Ljbffr
Candidatura e Ritorno (in fondo)
Ricevi annunci simili
Inserisci la tua email: ti avvisiamo quando escono nuovi annunci corrispondenti.
✅ Controlla la tua email e clicca il link per confermare l'alert.
Nessun account necessario. Disiscrizione con un clic dall'email.